Skewness

Skewness measures the asymmetry of a dataset’s distribution around its mean. It helps identify whether the data values are concentrated more on one side of the mean or are evenly spread.

Types of Skewness

1. Symmetrical Distribution (Zero Skewness):
   • The left and right sides of the distribution are mirror images.
   • Mean = Median = Mode.
2. Positive Skewness (Right-Skewed):
   • The tail on the right side (higher values) is longer.
   • Order: Mode < Median < Mean.
3. Negative Skewness (Left-Skewed):
   • The tail on the left side (lower values) is longer.
   • Order: Mean < Median < Mode.

Some important Measures of Skewness 

(i) Karl-Pearson coefficient of skewness 

According to Karl-Pearson the absolute measure of skewness = Mean – Mode.

Karl- Pearson coefficient of skewness = (Mean – Mode)/SD

(ii) Bowley’s coefficient of skewness 

(Q3+ Q1- 2Q2)/(Q3-Q1)

(iii) Coefficient of skewness based on moments